Machine Learning-Based traffic Crash Count Prediction
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Elsevier BV
Reference14 articles.
1. Chen, Mu-Ming and Chen, Mu-Chen. (2020) “Modeling Road Accident Severity with Comparisons of Logistic Regression, Decision Tree and Random Forest.” Information 11 (5): 270. URL: https://www.mdpi.com/2078-2489/11/5/270. ISSN: 2078-2489.
2. Parvareh, Maryam, Asrin Karimi, Satar Rezaei, Abraha Woldemichael, Sairan Nili, Bijan Nouri, and Nader Esmail Nasab. (2018) “Assessment and prediction of road accident injuries trend using time-series models in Kurdistan.” Burns & Trauma 6 (1): 111-118. ISSN: 2321-3876. DOI:10.1186/s41038-018-0111-6. URL: https://doi.org/10.1186/s41038-018-0111-6.
3. Alkheder, Sharaf, Madhar Taamneh, and Salah Taamneh. (2017) “Severity Prediction of traffic Accident Using an Artificial Neural Network.” Journal of Forecasting 36 (1): 100-108. ISSN: 0277-6693. DOI: https://doi.org/10.1002/for.2425. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/for.2425.
4. Cai, Qing, Jing Gan, Linheng Li, Dapeng Zhang, Ziwei Yi, and Qiaojun Xiang. (2020) “An Alternative Method for traffic Accident Severity Prediction: Using Deep Forests Algorithm.” Journal of Advanced Transportation 2020: 1257627. ISSN: 0197-6729. DOI: 10.1155/2020/1257627. URL: https://doi.org/10.1155/2020/1257627.
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